- Rmarkdown: cloned from https://github.com/micha-silver/ReLTER_demo
- Slides on website: https://micha-silver.github.io/index.html
- Youtube videos: (to be announced)
20/04/2022
Encourages collaboration “out of the box”.
setwd().RdataR scriptR packagesReLTER# Install some standard spatial packages from CRAN
if (!require("sf", quietly = TRUE))
install.packages(c("sf", "terra"))
# package from Bioconductor
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install()
BiocManager::install("EBImage")
## Warning: package(s) not installed when version(s) same as current; use `force = TRUE` to ## re-install: 'EBImage'
# Install development package from github
if (!require("remotes", quietly = TRUE))
install.packages("remotes")
if (!require("ReLTER", quietly = TRUE))
remotes::install_github("oggioniale/ReLTER")
## Registered S3 method overwritten by 'ggforce': ## method from ## scale_type.units units
## ## ## ReLTER is specially drafted for the LTER community. ## ## To contribute to the improvement of this package, join the group of ## developers (https://github.com/oggioniale/ReLTER). ## ## If you use this package, please cite as: ## ## Alessandro Oggioni, Micha Silver, Luigi Ranghetti & Paolo Tagliolato. ## (2021) oggioniale/ReLTER: ReLTER v1.0.0 (1.0.0). Zenodo. ## https://doi.org/10.5281/zenodo.5576813 ## ## Type 'citation(package = 'ReLTER')' on how to cite R packages in ## publications.
After installing, we need to load the packages into this R session.
# Convenient way to load list of packages
pkg_list <- c("sf", "terra", "ReLTER", "tmap")
lapply(pkg_list,require, character.only = TRUE)
## Loading required package: terra
## terra 1.5.21
## Loading required package: tmap
## [[1]] ## [1] TRUE ## ## [[2]] ## [1] TRUE ## ## [[3]] ## [1] TRUE ## ## [[4]] ## [1] TRUE
library(ReLTER)
maintainer("ReLTER")
## [1] "The package maintainer Alessandro Oggioni, phD (2020) <oggioniale@gmail.com>"
citation("ReLTER")
##
## To cite the 'ReLTER' package in publications use:
##
## Alessandro Oggioni, Micha Silver, Luigi Ranghetti & Paolo Tagliolato.
## (2021). oggioniale/ReLTER: ReLTER v1.0.0 (1.0.0). Zenodo.
## https://doi.org/10.5281/zenodo.5576813
##
## A BibTeX entry for LaTeX users is
##
## @Misc{,
## title = {oggioniale/ReLTER: ReLTER v1.0.0},
## author = {Alessandro Oggioni and Micha Silver and Luigi Ranghetti and Paolo Tagliolato},
## year = {2022},
## note = {R package version v1.0.0},
## }
ls("package:ReLTER")
## [1] "%>%" "get_activity_info" ## [3] "get_dataset_info" "get_ilter_envcharacts" ## [5] "get_ilter_generalinfo" "get_ilter_parameters" ## [7] "get_ilter_research_topics" "get_network_envcharacts" ## [9] "get_network_parameters" "get_network_related_resources" ## [11] "get_network_research_topics" "get_network_sites" ## [13] "get_site_info" "get_site_ODS" ## [15] "get_sos_procedurelist" "produce_network_points_map" ## [17] "produce_site_map" "produce_site_parameters_pie" ## [19] "produce_site_parameters_waffle" "produce_site_qrcode" ## [21] "taxon_id_pesi" "taxon_id_worms"
Search for DEIMS ID for a particular site. The function get_ilter_generalinfo allows to search by country name and site name. Then get_site_info() obtains various metadata about a chosen site.
donana = get_ilter_generalinfo(country_name = "Spain",
site_name = "Doñana")
(donana_id = donana$uri)
## [1] "https://deims.org/bcbc866c-3f4f-47a8-bbbc-0a93df6de7b2"
Plot a basic map of that site. We use the tmap package for viewing maps.
donana_polygon <- get_site_info(donana_id, category = "Boundaries") tm_basemap() + tm_shape(donana_polygon) + tm_fill(col = "blue", alpha = 0.3)
This example retrieves metadata from Lock Kinord in Scotland.
loch_kinord <- get_ilter_generalinfo(country_name = "United K",
site_name = "Loch Kinord")
(loch_kinord_id = loch_kinord$uri)
## [1] "https://deims.org/9fa171d2-5a24-40d3-9c06-b3f9e9d0f270"
loch_kinord_details <- get_site_info(loch_kinord_id,
c("Contacts", "EnvCharacts", "Parameters"))
print(paste("Site manager:",
loch_kinord_details$generalInfo.siteManager[[1]]['name'],
loch_kinord_details$generalInfo.siteManager[[1]]['email']))
## [1] "Site manager: Andrew Sier [Primary ECN contact] arjs@ceh.ac.uk"
# Metadata contact: (loch_kinord_details$generalInfo.metadataProvider[[1]]['name'])
## name ## 1 Andrew Sier [Primary ECN contact] ## 2 Caroline Dilks
print(paste("Average air temperature:",
loch_kinord_details$envCharacteristics.airTemperature.avg))
## [1] "Average air temperature: 6.62"
print(paste("Annual precipitation:",
loch_kinord_details$envCharacteristics.precipitation.annual))
## [1] "Annual precipitation: 1031.3"
print(paste("GeoBonBiome:",
loch_kinord_details$envCharacteristics.geoBonBiome[[1]]))
## [1] "GeoBonBiome: Fresh water lakes"
# Parameters:" head(loch_kinord_details$parameter[[1]]['parameterLabel'], 12)
## parameterLabel ## 1 ammonium content ## 2 benthic invertebrates abundance ## 3 benthic invertebrates presence ## 4 conductivity ## 5 dissolved nutrient ## 6 dissolved organic carbon in water ## 7 ecosystem parameter ## 8 inorganic nutrient content ## 9 lake level ## 10 lake temperature ## 11 nitrogen content ## 12 species abundance
The LTER network in Slovakia
lter_slovakia_id = "https://deims.org/networks/3d6a8d72-9f86-4082-ad56-a361b4cdc8a0" network_research_topics <- get_network_research_topics(lter_slovakia_id) head(network_research_topics$researchTopicsLabel, 20)
## [1] "animal ecology" "biodiversity" "biology" ## [4] "climate change" "climate monitoring" "climatology" ## [7] "community dynamics" "community ecology" "ecology" ## [10] "ecosystem ecology" "ecosystem function" "ecosystem service" ## [13] "forest ecology" "history" "land use history" ## [16] "meteorology" "phenology" "plant ecology" ## [19] "population dynamics" "population ecology"
lter_slovakia_sites <- get_network_sites(lter_slovakia_id) lter_slovakia_sites$title
## [1] "Bab - Slovakia" ## [2] "Jalovecka dolina - Slovakia" ## [3] "Kralova hola - Slovakia" ## [4] "Kremnicke vrchy Ecological Experimental Station - Slovakia" ## [5] "Polana Biosphere Reserve (Hukavsky grun) - Slovakia" ## [6] "Poloniny National Park LTSER - Slovakia" ## [7] "Tatra National Park - Slovakia" ## [8] "Tatras - alpine summits - Slovakia" ## [9] "Trnava LTSER - Slovakia"
lter_slovakia <- produce_network_points_map(lter_slovakia_id, "SVK")
svk <- readRDS("gadm36_SVK_0_sp.rds") # downloaded by produce_network_points_map()
tm_basemap() +
tm_shape(lter_slovakia) +
tm_dots(col = "blue", size=0.04) +
tm_shape(svk) +
tm_borders(col = "purple", lwd = 0.6) +
tm_grid(alpha = 0.4) +
tm_scale_bar(position = c("right", "bottom"))
ReLTER relies on the data entered into DEIMS-SDR. However sometimes there are:
Query for Site Manager
# Multiple sites in the KISKUN region of Hungary
kiskun <- get_ilter_generalinfo(country_name = "Hungary",
site_name = "KISKUN")
# How many sites?
print(paste("In Kiskun region: ", length(kiskun$title), "sites"))
## [1] "In Kiskun region: 8 sites"
(kiskun$title)
## [1] "Kiskun Forest Reserve Sites, KISKUN LTER - Hungary" ## [2] "VULCAN Kiskunsag, KISKUN LTER - Hungary" ## [3] "Kiskun Restoration Experiments, KISKUN LTER - Hungary" ## [4] "Kiskun Site Network (Jedlik), KISKUN LTER - Hungary" ## [5] "KISKUN LTER - Hungary" ## [6] "LTER Fulophaza Site, KISKUN LTER - Hungary" ## [7] "Bugac-Bocsa-Orgovany Site, KISKUN LTER - Hungary" ## [8] "Orgovany Site, KISKUN LTER - Hungary"
# Which site? Bugac-Bocsa bugac_id <- kiskun[7,]$uri bugac_details <- get_site_info(bugac_id,"Contacts") (bugac_details$generalInfo.siteManager[[1]]['name'])
## name ## 1 Gábor Ónodi
Now query for boundary
bugac_polygon <- get_site_info(bugac_id, "Boundaries")
## ## ---- ## This site does not have boundaries uploaded to DEIMS-SDR. ## Please verify in the site page: https://deims.org/609e5959-8cd8-44a0-ab42-eda521cd452a ## ----
str(bugac_polygon)
## tibble [1 × 9] (S3: tbl_df/tbl/data.frame) ## $ title : chr "Bugac-Bocsa-Orgovany Site, KISKUN LTER - Hungary" ## $ uri : chr "https://deims.org/609e5959-8cd8-44a0-ab42-eda521cd452a" ## $ boundaries : logi NA ## $ geoCoord : chr "POINT (19.5281 46.7183)" ## $ country :List of 1 ## ..$ : chr "Hungary" ## $ geoElev.avg : int 112 ## $ geoElev.min : int 105 ## $ geoElev.max : int 120 ## $ geoElev.unit: chr "msl"
# No geometry
paradiso <- get_ilter_generalinfo(country_name = "Italy",
site_name = "Gran Paradiso")
(paradiso$title)
## [1] "IT23 - Gran Paradiso National Park - Italy" ## [2] "Gran Paradiso National Park - Italy"
# Choose the second paradiso_id <- paradiso[2,]$uri paradiso_details <- get_site_info(paradiso_id,"Contacts") # Multiple names for metadata: paradiso_details$generalInfo.metadataProvider[[1]]['name']
## name ## 1 Alessandro Oggioni ## 2 Ramona Viterbi
# But what about funding agency paradiso_details$generalInfo.fundingAgency
## [1] NA
Functions within ReLTER help to acquire certain Earth Observation datasets. The get_site_ODS() function offers to ReLTER users access to the OpenDataScience Europe (ODS) archive (https://maps.opendatascience.eu/) with landcover, NDVI, natura2000, Corine landcover, and OSM features, all at 30 meter pixel resolution. Cropping to site boundaries is done in the cloud, and due to the Cloud Optimized Geotiff (COG) format, downloads are quite small.
# Get DEIMS ID for Kis-Balaton site
kis_balaton <- get_ilter_generalinfo(country_name = "Hungary",
site_name = "Kis-Balaton")
kb_id = kis_balaton$uri
kb_polygon = get_site_info(kb_id, "Boundaries")
# Now acquire landcover and NDVI from ODS
kb_landcover = get_site_ODS(kb_id, dataset = "landcover")
kb_ndvi_summer = get_site_ODS(kb_id, "ndvi_summer")
# Plot maps tm_basemap() + tm_shape(kb_polygon) + tm_borders(col = "purple") + tm_shape(kb_ndvi_summer) + tm_raster(alpha=0.7, palette = "RdYlGn")
tm_basemap() + tm_shape(kb_polygon) + tm_borders(col = "purple") + tm_shape(kb_landcover) + tm_raster(alpha=0.7, palette = "Set1")
lezirias <- get_ilter_generalinfo(country_name = "Portugal",
site_name = "Companhia")
lezirias_id = lezirias$uri
lezirias_polygon = get_site_info(lezirias_id, "Boundaries")
# Now acquire spring NDVI from OSD
lezirias_ndvi_spring = get_site_ODS(lezirias_id, "ndvi_spring")
# Plot maps tm_basemap() + tm_shape(lezirias_polygon) + tm_borders(col = "purple") + tm_shape(lezirias_ndvi_spring) + tm_raster(alpha=0.7, palette = "RdYlGn")
# The function outputs a raster. We can save to Geotiff for use in other GIS class(lezirias_ndvi_spring)
## [1] "SpatRaster" ## attr(,"package") ## [1] "terra"
writeRaster(x = lezirias_ndvi_spring,
filename = "lezirias_ndvi_spring.tif",
overwrite = TRUE)
ReLTER has implemented some revealing visualizations of the various parameters collected at LTER sites. One visualization is the pie chart of environmental parameters.
In an example above the DEIMS ID of Kis Balaton (Kiskun LTER) was found. We’ll use that site to show a pie chart of environmental variables collected in that site.
produce_site_parameters_pie(kb_id)
## # A tibble: 8 × 9 ## parameterGroups n freq label end start middle hjust vjust ## <chr> <int> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 agricultural parameter 1 0.0208 2% 0.131 0 0.0654 0 0 ## 2 atmospheric parameter 1 0.0208 2% 0.262 0.131 0.196 0 0 ## 3 biological parameter 16 0.333 33% 2.36 0.262 1.31 0 0 ## 4 chemical parameter 16 0.333 33% 4.45 2.36 3.40 1 1 ## 5 ecosystem parameter 8 0.167 17% 5.50 4.45 4.97 1 0 ## 6 physical parameter 1 0.0208 2% 5.63 5.50 5.56 1 0 ## 7 soil parameter 1 0.0208 2% 5.76 5.63 5.69 1 0 ## 8 water parameter 4 0.0833 8% 6.28 5.76 6.02 1 0
Similarly, a “waffle” chart can be produced.
produce_site_parameters_waffle(kb_id)
## # A tibble: 8 × 4 ## parameterGroups n freq label ## <chr> <int> <dbl> <chr> ## 1 agricultural parameter 1 0.0208 2% ## 2 atmospheric parameter 1 0.0208 2% ## 3 biological parameter 16 0.333 33% ## 4 chemical parameter 16 0.333 33% ## 5 ecosystem parameter 8 0.167 17% ## 6 physical parameter 1 0.0208 2% ## 7 soil parameter 1 0.0208 2% ## 8 water parameter 4 0.0833 8%
This example uses the LTER network in Greece. Call the produce_network_points_map() function (requires both DEIMS network ID and the three letter ISO code for the country to be mapped) to get all sites in a country.
lter_greece_id = "https://deims.org/networks/83453a6c-792d-4549-9dbb-c17ced2e0cc3"
lter_greece <- produce_network_points_map(lter_greece_id, "GRC")
grc <- readRDS("gadm36_GRC_0_sp.rds") # available from `produce_network_points_map()
tm_basemap("OpenStreetMap.Mapnik") +
tm_shape(lter_greece) +
tm_dots(col = "blue", size=0.08) +
tm_shape(grc) +
tm_borders(col = "purple", lwd=2) +
tm_grid(alpha = 0.4) +
tm_scale_bar(position = c("right", "bottom"))